SOURCE-LINKED INTELLIGENCE

Off-axis crack arrest by harnessing micro- and mesostructural design

CORDIS · observation · Publication date unknown

ates will set the foundations to unravel the root causes. This is supported by the development and experimental validation of an efficient 3D numerical model that bridges the micro- and mesoscale via deep learning. Once validated, genetic algorithms will mimic evolutionary trial-and-error to optimise the established working principles and maximise crack arrest. The designed patterns will then be manufactured using a novel, scalable imprinting process or established processes such as tailored fibre placement and laser cutting. CRACKAR will showcase that careful experimental validation of a multiscale model can revolutionise mechanistic understanding. This achievement would yield profound gains for composites and materials research as a whole, enabling us to tailor the material to the loading scenario. Crack development, Fibre-reinforced composites, Radiography, Computed tomography, Micro- and mesomechanics

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recordType

award

status

SIGNED

region

EU

value

2573125

unit

EUR